“Sales managers prefer graduates who are academic, with some interest in finance but more social skills with extra-curricular activities e.g. being the Head of the rugby/cricket club. They’re less fussy on the degree subject, but quite fussy in terms of the university they have attended – Oxford, Cambridge, LSE, Imperial.

The [derivatives] trading/research side is much more focussed on the technical. Many of our senior managers are from French universities, with experience of engineering schools and écoles polytechniques in France. They look for expertise in engineering, maths, qualitative [quantitative?] finance. They like Oxford, Cambridge, Warwick”.

"Instead of reviewing the bank’s risk management systems, the executive directors would have ndless meetings discussing the corporate dress code as Fuld was a stickler for appearances. A angerous lack of awareness about the technical financial products the bank was playing with didn’t elp matters."

Most people employed in finance are involved in sales and marketing activity, and so the soft skills needed for these roles are frequently highlighted by employers to the likes of the FSSC and Universities. However, the core of the banks' business is is highly quantitative, to quote from p 14 of the FSSC report:

“…[banks] need high level maths skills because that’s how the bank makes money – vanilla roducts have very little margin.”

The financial innovation (or more accurately, the re-introduction of derivative products into financial markets) since the 1970s has changed the nature of banking, has the culture of banking kept up?

Perhaps a solution is to separate financial institutions into "traditional banks", undertaking lending and M&A activities relying on sales and marketing skills and "speculative banks" specialising in trading, derivatives and risk management. However, this is not the only model. Many manufacturing firms, particularly pharmaceutical and oil companies, are based on core expertise in science and engineering but where the majority of employees are involved in sales and marketing. So it appears the cultures can co-exist.

Wednesday, 26 August 2009

On of my favourite quotes from the credit crisis comes from the 2/02/08 edition of The Economist, the article "No Defense" on fraud issues at Societe General, states

"In common with other French banks, SocGen was also thought by many to take an overly mathematical approach to risk. “‘It may work in practice but does it work in theory?' is the stereotype of a French bank,” says one industry consultant."

Dear Sir
The article "Of couples and copulas", published on 24 April 2009,
suggests that David Li's formula is to blame for the current financial
crisis. For me, this is akin to blaming Einstein's E=mc² formula for
the destruction wreaked by the atomic bomb.

Feeling like a risk manager whose protestations of imminent danger
were ignored, I wish to make clear that many well-respected
academics have pointed out the limitations of the mathematical tools
used in the finance industry, including Li's formula. However, these
warnings were either ignored or dismissed with a desultory
response: "It's academic".

We hope that we are listened to in the future, rather than being
made a convenient scapegoat.

The Royal Society published a report on Science, Technology, Engineering and Maths impact on the service sector. They devote a whole chapter (3) to financial innovation, see Hidden Wealth. The report was covered in the FT.

I was contact by the Royal Society in mid-July, this is (their) summary of what I said:

1. The financial crisis was not a homogeneous events; some institutions did (much) better than thers.

2. The root of the problem is in banks mis-pricing assets. When pricing assets the banks were relying on mathematical models. Some banks had "engineered" their own models, others "bought in" models (either by buying "off the shelf" or by hiring individuals from the innovating banks). Banks who treated models as "black boxes" have done far worse than those that had a reputation or developing their own.

3. Many quants (the majority ?) have a background in physics and engineering (there is a factoid that the majority of engineering graduates from top UK universities go into finance rather than engineering - you could check this. Similarly The City is the largest employer of physics PhDs). They understand deterministic systems but only have a rudimentary understanding of modern probability theory (the majority of maths graduates are in a very similar position, I spoke to a maths teacher who had a degree from Glasgow who told me he had not done probability since he was 16).

4. Financial economics developed in the late twentieth century using relatively straightforward maths. The models it produced are "too simple" (see pp 4-12 in "An Engine, Not a Camera"), but are "elegant".

The physicists / engineers were given a simple framework in which deterministic approaches appeared to give definite results. This approach is related to the "Crash of 87" and "When genius failed" in '98.

5. Throughout the industry a belief emerged that maths, "rocket science" removed risk. In the 1990s, mathematicians began to investigate financial models and re-evaluate them. A more rigorous approach to financial economics revealed the naivety of the assumptions that led to the simple models.

6. Because the financial mathematics community is small and peripheral in British science, it lacks authority , and the theory (from the mathematicians) became disconnected from the practice in industry.

7. In Europe, because they approach probability as a branch of analysis rather than from the perspective of statistics, there seems to have been a better appreciation that simple models that fitted data were inadequate. This is a subtle point. The issue is whether the "quants"
really understand stochastic systems. Does the UK education system (schools to universities) produce the volume of people with (basic to advanced) skills in probability and statistics. There is a view that France & Germany are better at this, as demonstrated by the large number of continental scientists and engineers employed in London banks.

8. The credit crisis provides a tangible example and introduction to a wider problem about our poor understandings of complex and stochastic systems. The concern is that many of the global challenges we face involve these sorts of systems. Is our science up to the task?

9. There is a basic competency issue but also a need to develop new mathematics able to describe what Lord May describes as "ephemeral" systems, but in other areas relating to fundamental maths.

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About Me

I am a Lecturer in Financial Mathematics at Heriot-Watt University in Edinburgh. Heriot-Watt was the first UK university to offer degrees in Actuarial Science and Financial Mathematics and is a leading UK research centre in the fields.

Between 2006-2011 I was the UK Research Council's Academic Fellow in Financial Mathematics and was involved in informing policy makers of mathematical aspects of the Credit Crisis.